Failure detection of dual-redundancy BLDC motor based on wavelet transform

In order to improve the reliability of the system, a dual-redundancy high-voltage brushless DC motor is designed. According to the structural features of dual-redundancy brushless DC motor, the mathematical model is built up. Methods of motor fault detection are studied. The fault signal is analysized by fourier transform. For the deficiency of Fourier transform, a fault detection using wavelet transform method is proposed. The current is determined to the fault detection signal based on the motor fault tree. The coif 5 is selected as the wavelet basis function. Through the analysis of motor failures, the characteristics of the winding open circuit, a phase with Hall for high and low are obtained by the coif 5 wavelet function. The fault feature vectors are obtained by the layer 2 decomposition coefficients.